Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control

Hiroyuki OKUDA; Nobuto SUGIE; Tatsuya SUZUKI; Kentaro HARAGUCHI; Zibo KANG

doi:10.1587/transinf.2020EDP7039

IEICE TRANSACTIONS on Information

Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control

Hiroyuki OKUDA, Nobuto SUGIE, Tatsuya SUZUKI, Kentaro HARAGUCHI, Zibo KANG

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Path planning and motion control are fundamental components to realize safe and reliable autonomous driving. The discrimination of the role of these two components, however, is somewhat obscure because of strong mathematical interaction between these two components. This often results in a redundant computation in the implementation. One of attracting idea to overcome this redundancy is a simultaneous path planning and motion control (SPPMC) based on a model predictive control framework. SPPMC finds the optimal control input considering not only the vehicle dynamics but also the various constraints which reflect the physical limitations, safety constraints and so on to achieve the goal of a given behavior. In driving in the real traffic environment, decision making has also strong interaction with planning and control. This is much more emphasized in the case that several tasks are switched in some context to realize higher-level tasks. This paper presents a basic idea to integrate decision making, path planning and motion control which is able to be executed in realtime. In particular, lane-changing behavior together with the decision of its initiation is selected as the target task. The proposed idea is based on the nonlinear model predictive control and appropriate switching of the cost function and constraints in it. As the result, the decision of the initiation, planning, and control of the lane-changing behavior are achieved by solving a single optimization problem under several constraints such as safety. The validity of the proposed method is tested by using a vehicle simulator.

Publication: IEICE TRANSACTIONS on Information Vol.E103-D No.12 pp.2632-2642

Publication Date: 2020/12/01

Publicized: 2020/08/31

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2020EDP7039

Type of Manuscript: PAPER

Category: Artificial Intelligence, Data Mining

Authors

Hiroyuki OKUDA
  Nagoya University
Nobuto SUGIE
  Nagoya University
Tatsuya SUZUKI
  Nagoya University
Kentaro HARAGUCHI
  Toyota Technical Development Corporation
Zibo KANG
  Toyota Technical Development Corporation

Keyword

model predictive control, simultaneous path planning and motion control, lane-changing

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Hiroyuki OKUDA, Nobuto SUGIE, Tatsuya SUZUKI, Kentaro HARAGUCHI, Zibo KANG, "Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control" in IEICE TRANSACTIONS on Information, vol. E103-D, no. 12, pp. 2632-2642, December 2020, doi: 10.1587/transinf.2020EDP7039.
Abstract: Path planning and motion control are fundamental components to realize safe and reliable autonomous driving. The discrimination of the role of these two components, however, is somewhat obscure because of strong mathematical interaction between these two components. This often results in a redundant computation in the implementation. One of attracting idea to overcome this redundancy is a simultaneous path planning and motion control (SPPMC) based on a model predictive control framework. SPPMC finds the optimal control input considering not only the vehicle dynamics but also the various constraints which reflect the physical limitations, safety constraints and so on to achieve the goal of a given behavior. In driving in the real traffic environment, decision making has also strong interaction with planning and control. This is much more emphasized in the case that several tasks are switched in some context to realize higher-level tasks. This paper presents a basic idea to integrate decision making, path planning and motion control which is able to be executed in realtime. In particular, lane-changing behavior together with the decision of its initiation is selected as the target task. The proposed idea is based on the nonlinear model predictive control and appropriate switching of the cost function and constraints in it. As the result, the decision of the initiation, planning, and control of the lane-changing behavior are achieved by solving a single optimization problem under several constraints such as safety. The validity of the proposed method is tested by using a vehicle simulator.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020EDP7039/_p

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@ARTICLE{e103-d_12_2632,
author={Hiroyuki OKUDA, Nobuto SUGIE, Tatsuya SUZUKI, Kentaro HARAGUCHI, Zibo KANG, },
journal={IEICE TRANSACTIONS on Information},
title={Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control},
year={2020},
volume={E103-D},
number={12},
pages={2632-2642},
abstract={Path planning and motion control are fundamental components to realize safe and reliable autonomous driving. The discrimination of the role of these two components, however, is somewhat obscure because of strong mathematical interaction between these two components. This often results in a redundant computation in the implementation. One of attracting idea to overcome this redundancy is a simultaneous path planning and motion control (SPPMC) based on a model predictive control framework. SPPMC finds the optimal control input considering not only the vehicle dynamics but also the various constraints which reflect the physical limitations, safety constraints and so on to achieve the goal of a given behavior. In driving in the real traffic environment, decision making has also strong interaction with planning and control. This is much more emphasized in the case that several tasks are switched in some context to realize higher-level tasks. This paper presents a basic idea to integrate decision making, path planning and motion control which is able to be executed in realtime. In particular, lane-changing behavior together with the decision of its initiation is selected as the target task. The proposed idea is based on the nonlinear model predictive control and appropriate switching of the cost function and constraints in it. As the result, the decision of the initiation, planning, and control of the lane-changing behavior are achieved by solving a single optimization problem under several constraints such as safety. The validity of the proposed method is tested by using a vehicle simulator.},
keywords={},
doi={10.1587/transinf.2020EDP7039},
ISSN={1745-1361},
month={December},}

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TY - JOUR
TI - Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control
T2 - IEICE TRANSACTIONS on Information
SP - 2632
EP - 2642
AU - Hiroyuki OKUDA
AU - Nobuto SUGIE
AU - Tatsuya SUZUKI
AU - Kentaro HARAGUCHI
AU - Zibo KANG
PY - 2020
DO - 10.1587/transinf.2020EDP7039
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2020
AB - Path planning and motion control are fundamental components to realize safe and reliable autonomous driving. The discrimination of the role of these two components, however, is somewhat obscure because of strong mathematical interaction between these two components. This often results in a redundant computation in the implementation. One of attracting idea to overcome this redundancy is a simultaneous path planning and motion control (SPPMC) based on a model predictive control framework. SPPMC finds the optimal control input considering not only the vehicle dynamics but also the various constraints which reflect the physical limitations, safety constraints and so on to achieve the goal of a given behavior. In driving in the real traffic environment, decision making has also strong interaction with planning and control. This is much more emphasized in the case that several tasks are switched in some context to realize higher-level tasks. This paper presents a basic idea to integrate decision making, path planning and motion control which is able to be executed in realtime. In particular, lane-changing behavior together with the decision of its initiation is selected as the target task. The proposed idea is based on the nonlinear model predictive control and appropriate switching of the cost function and constraints in it. As the result, the decision of the initiation, planning, and control of the lane-changing behavior are achieved by solving a single optimization problem under several constraints such as safety. The validity of the proposed method is tested by using a vehicle simulator.
ER -

IEICE TRANSACTIONS on Information